摘要
PSO算法是一种基于群体智能的群优化和群搜索算法,效率高、收敛快。提出将其与K-means算法结合,用于网络入侵检测。实验表明,PSO-based K-means算法克服了K-means算法对初始聚类中心、孤立点和噪声敏感且易陷入局部最优解的缺点,收敛速度快,检测准确率较高。
PSO is an algorithm based on swarm intelligence optimization and search, has high efficiency, fast conver- gence. In this paper, it combines with the K-means algorithm for network intrusion detection. Experiment shows that PSO-based K-means algorithm overcomes the shortcoming that the K-means algorithm is sensitive to the initial cluster centers, outliers and noise, easy to fall into local optimal solution. It＇s an algorithm with fast convergence and higher de- tection accuracy.
出处
《计算机科学》
CSCD
北大核心
2013年第11期137-139,共3页
Computer Science
基金
国家发改委发改办[2012]3179号下一代互联网络扫描与补丁管理系统产业化项目基金资助
